Recently there has been a sharp increase in the use of wireless communication devices, such as mobile phones, in the car. Such dialing while driving situation fits the classic definition of a hands busy, eyes busy task. Speech recognition is a natural and effective solution. Not only convenience, but also safety concerns motivate the use of voice technology in this situation. Other than mobile phones, as PDA (personal digital assistance) devices become smaller, input becomes more difficult. Speech recognition is a natural way to interact with these small devices because button or touch screens are not feasible or too expensive. All those devices are battery powered. Continuous speech recognition is a resource intensive algorithm. Commercial dictation software requires more than 10 M bytes to install on a disk and 32M bytes RAM to run the applications. A typical embedded system can not afford this much RAM because of its high cost and power consumption. It also lacks disk to store the large amount of static data (acoustic models). A 32-bit, floating point CPU with lots of memory is too expensive and drains too much power. Most of these embedded fixed point processor devices use a 16-bit, fixed point CPU with only on chip memory. It is highly desirable to fit a speech recognition algorithm on such a device without performance degradation or sacrificing functionality.
A most challenging condition is to provide this for hands free digit dialing in a highway driving condition.